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Tuesday, July 29, 2014

I have a new candidate for coolest research institute architecture. HKUST's Institute for Advanced Study is housed in an amazing building with a view of Clearwater Bay in HK. The members of the institute will be mostly theoretical physicists and mathematicians :-)

Monday, July 28, 2014

This paper provides additional support that the GWAS hits found by SSGAC affect cognitive ability. My guess is that UK age 14 SATS scores are pretty g-loaded. Note this is an ethnically homogeneous sample of students.

If the effect size per allele is about 1/30 SD, it would take ~1000 to account for normal population variation. These are the first loci detected, so typical effect size of alleles affecting cognitive ability is probably smaller. This seems consistent with my estimate of ~10k causal variants.

Genome-wide association study results have yielded evidence for the association of common genetic variants with crude measures of completed educational attainment in adults. Whilst informative, these results do not inform as to the mechanism of these effects or their presence at earlier ages and where educational performance is more routinely and more precisely assessed. Single nucleotide polymorphisms exhibiting genome-wide significant associations with adult educational attainment were combined to derive an unweighted allele score in 5,979 and 6,145 young participants from the Avon Longitudinal Study of Parents and Children with key stage 3 national curriculum test results (SATS results) available at age 13 to 14 years in English and mathematics respectively. Standardised (z-scored) results for English and mathematics showed an expected relationship with sex, with girls exhibiting an advantage over boys in English (0.433 SD (95%CI 0.395, 0.470), p<10−10) with more similar results (though in the opposite direction) in mathematics (0.042 SD (95%CI 0.004, 0.080), p = 0.030). Each additional adult educational attainment increasing allele was associated with 0.041 SD (95%CI 0.020, 0.063), p = 1.79×10−04 and 0.028 SD (95%CI 0.007, 0.050), p = 0.01 increases in standardised SATS score for English and mathematics respectively. Educational attainment is a complex multifactorial behavioural trait which has not had heritable contributions to it fully characterised. We were able to apply the results from a large study of adult educational attainment to a study of child exam performance marking events in the process of learning rather than realised adult end product. Our results support evidence for common, small genetic contributions to educational attainment, but also emphasise the likely lifecourse nature of this genetic effect. Results here also, by an alternative route, suggest that existing methods for child examination are able to recognise early life variation likely to be related to ultimate educational attainment.

Saturday, July 26, 2014

I came across this nice discussion at LessWrong which is similar to my old post Success vs Ability. The illustration below shows why even a strong predictor of outcome is seldom able to pick out the very top performer: e.g., taller people are on average better at basketball, but the best player in the world is not the tallest; smarter people are on average better at making money, but the richest person in the world is not the smartest, etc.

This seems like a trivial point (as are most things, when explained clearly), however, it still eludes the vast majority. For example, in the Atlantic article I linked to in the earlier post Creative Minds, the neuroscientist professor who studies creative genius misunderstands the implications of the Terman study. She repeats the common claim that Terman's study fails to support the importance of high cognitive ability to "genius"-level achievement: none of the Termites won a Nobel prize, whereas Shockley and Alvarez, who narrowly missed the (verbally loaded) Stanford-Binet cut for the study, each won for work in experimental physics. But luck, drive, creativity, and other factors, all at least somewhat independent of intelligence, influence success in science. Combine this with the fact that there are exponentially more people a bit below the Terman cut than above it, and Terman's results do little more than confirm that cognitive ability is positively but not perfectly correlated with creative output.

In the SMPY study probability of having published a literary work or earned a patent was increasing with ability even within the top 1%. The "IQ over 120 doesn't matter" meme falls apart if one measures individual likelihood of success, as opposed to the total number of individuals at, e.g., IQ 120 vs IQ 145, who have achieved some milestone. The base population of the former is 100 times that of the latter!

This topic came up last night in Hong Kong, at dinner with two hedge funders (Caltech/MIT guys with PhDs) who have had long careers in finance. Both observed that 20 years ago it was nearly impossible to predict which of their colleagues and peers would go on to make vast fortunes, as opposed to becoming merely rich.

Tuesday, July 22, 2014

The Scientist: ... The researchers, led by Kamel Khalili at Temple University in Philadelphia, Pennsylvania, used the CRISPR/Cas9 genome-editing system to excise HIV from several human cell lines, including microglia and T cells. They targeted both the 5’ and 3’ ends of the virus, called the long terminal repeats (LTRs), so that the entire viral genome was removed.

“We were extremely happy with the outcome,” Khalili told The Scientist. “It was a little bit . . . mind-boggling how this system really can identify a single copy of the virus in a chromosome, which is highly packed DNA, and exactly cleave that region.”

His team showed that not only could Cas9 excise one copy of the HIV genome, but—operating in the same cell—it could also clip out another copy lurking in a different chromosome. Often, Khalili said, a cell can have several copies of latent HIV distributed across various chromosomes. “Most likely the technology is going to clean up the viral DNA” in a cell, he said.

... One limitation of the CRISPR/Cas9 approach is that it can chop up unintended regions of the genome, producing so-called off-target effects. Khalili’s group performed whole-genome sequencing to look for off-target effects, but didn’t find any. T.J. Cradick, the director of the protein engineering core facility at Georgia Tech, said that a more thorough analysis of potential off-target effects is still required to make sure nothing has been overlooked. Nonetheless, “latent HIV provirus is a very exciting target and . . . a very promising way forward,” said Cradick, who did not participate in the study.

Monday, July 21, 2014

The Atlantic: ... One after another, my writer subjects came to my office and spent three or four hours pouring out the stories of their struggles with mood disorder—mostly depression, but occasionally bipolar disorder. A full 80 percent of them had had some kind of mood disturbance at some time in their lives, compared with just 30 percent of the control group—only slightly less than an age-matched group in the general population. (At first I had been surprised that nearly all the writers I approached would so eagerly agree to participate in a study with a young and unknown assistant professor—but I quickly came to understand why they were so interested in talking to a psychiatrist.)

The Vonneguts turned out to be representative of the writers’ families, in which both mood disorder and creativity were overrepresented—as with the Vonneguts, some of the creative relatives were writers, but others were dancers, visual artists, chemists, architects, or mathematicians. This is consistent with what some other studies have found. When the psychologist Kay Redfield Jamison looked at 47 famous writers and artists in Great Britain, she found that more than 38 percent had been treated for a mood disorder; the highest rates occurred among playwrights, and the second-highest among poets. When Joseph Schildkraut, a psychiatrist at Harvard Medical School, studied a group of 15 abstract-expressionist painters in the mid-20th century, he found that half of them had some form of mental illness, mostly depression or bipolar disorder; nearly half of these artists failed to live past age 60.
...

This time around, I wanted to examine a more diverse sample of creativity, from the sciences as well as the arts. My motivations were partly selfish—I wanted the chance to discuss the creative process with people who might think and work differently, and I thought I could probably learn a lot by listening to just a few people from specific scientific fields. After all, each would be an individual jewel—a fascinating study on his or her own. Now that I’m about halfway through the study, I can say that this is exactly what has happened. My individual jewels so far include, among others, the filmmaker George Lucas, the mathematician and Fields Medalist William Thurston, the Pulitzer Prize–winning novelist Jane Smiley, and six Nobel laureates from the fields of chemistry, physics, and physiology or medicine. Because winners of major awards are typically older, and because I wanted to include some younger people, I’ve also recruited winners of the National Institutes of Health Pioneer Award and other prizes in the arts.

Apart from stating their names, I do not have permission to reveal individual information about my subjects. And because the study is ongoing (each subject can take as long as a year to recruit, making for slow progress), we do not yet have any definitive results—though we do have a good sense of the direction that things are taking. By studying the structural and functional characteristics of subjects’ brains in addition to their personal and family histories, we are learning an enormous amount about how creativity occurs in the brain, as well as whether these scientists and artists display the same personal or familial connections to mental illness that the subjects in my Iowa Writers’ Workshop study did.
...

As I hypothesized, the creative people have shown stronger activations in their association cortices during all four tasks than the controls have. (See the images on page 74.) This pattern has held true for both the artists and the scientists, suggesting that similar brain processes may underlie a broad spectrum of creative expression. Common stereotypes about “right brained” versus “left brained” people notwithstanding, this parallel makes sense. Many creative people are polymaths, people with broad interests in many fields—a common trait among my study subjects.

Saturday, July 19, 2014

The host is Harvard professor Harvey Mansfield. I'm not sure who all of the other panelists are, but they seem to include a professor of government and another of economics. The Asian physics guy is probably Peter Lu.

The Program on Constitutional Government at Harvard University

March 14, 2014: Charles Murray, on “The Bell Curve Revisited.” Charles Murray is a Fellow at the American Enterprise Association, and the author of famous and influential books, among them, Losing Ground (1984), The Bell Curve; Intelligence and Class Structure in American Life (1994, with Richard Herrnstein), and most recently, Coming Apart: the State of White America,1960-2010 (2013). He declares himself a libertarian, has written for many journals, and has received the Irving Kristol award from AEI and the Bradley Prize from the Bradley Foundation. He is Harvard ’65 and received a PhD in political science from M. I. T. in 1974. He is also the author of several “Murray’s laws” of social behavior.

TechnologyReview: The British government says that it plans to hire the U.S. gene-sequencing company Illumina to sequence 100,000 human genomes in what is the largest national project to decode the DNA of a populace. ...

Some other countries are also considering large national sequencing projects. The U.K. project will focus on people with cancer, as well as adults and children with rare diseases. Because all Britons are members of the National Health Service, the project expects to be able to compare DNA data with detailed centralized health records (see “Why the U.K. Wants a Genomic National Health Service”).

While the number of genomes to be sequenced is 100,000, the total number of Britons participating in the study is smaller, about 70,000. That is because for cancer patients Genomics England intends to obtain the sequence of both their inherited DNA as well as that of their cancers.

BGI bid for this work but their transition to the upgraded Complete Genomics technology is still in progress. This delay has affected our cognitive genomics project as well.

Big data sets are also being assembled in the US (note in this case only SNP genotyping; cost is less than $100 per person now):

AKESOgen announced today that it has been awarded a $7.5M contract by the U.S. Department of Veterans Affairs (VA) for genotyping samples from U.S. veterans as part of the Million Veteran Program (MVP). This award covers the genotyping of 105,000 veterans in the first year of a five year contract.

"The VA's Million Veteran Program is one of the largest genetic initiatives ever undertaken in the US and its visionary genomics and genetics approach will provide new insights about how genes affect health. The goal is to improve healthcare for veterans by understanding the genetic basis of many common conditions. The data will ultimately be beneficial to the healthcare of all veterans and of the wider community. We are delighted to have been selected by the VA for this unique endeavor and we will provide genetic data of the highest quality to the VA." said Bob Boisjoli, CEO of AKESOgen. To fulfill the VA contract, AKESOgen will utilize a custom designed array based genotyping solution from Affymetrix, Inc. ...

My prediction is that of order a million phenotype:genotype pairs will be enough to deduce the genetic architecture of complex traits such as height or cognitive ability. SNPs will be enough to solve most of the problem, so that cost is now ~ $100M or less -- interested billionaires please contact me :-)

Friday, July 11, 2014

HLMI = ‘high–level machine intelligence’ = one that can carry out most human professions at least as well as a typical human. I'm more pessimistic than the average researcher in the poll. My 95 percent confidence interval has earliest HLMI about 50 years from now, putting me at ~ 80-90th percentile in this group as far as pessimism. I think human genetic engineering will be around for at least a generation or so before machines pass a "strong" Turing test. Perhaps a genetically enhanced team of researchers will be the ones who finally reach the milestone, ~ 100 years after Turing proposed it :-)

These are the days of miracle and wonder
This is the long-distance call
The way the camera follows us in slo-mo
The way we look to us all
The way we look to a distant constellation
That’s dying in a corner of the sky
These are the days of miracle and wonder
And don’t cry baby don’t cry
Don’t cry -- Paul Simon

Abstract: In some quarters, there is intense concern about high–level machine intelligence and superintelligent AI coming up in a few decades, bringing with it significant risks for humanity; in other quarters, these issues are ignored or considered science fiction. We wanted to clarify what the distribution of opinions actually is, what probability the best experts currently assign to high–level machine intelligence coming up within a particular time–frame, which risks they see with that development and how fast they see these developing. We thus designed a brief questionnaire and distributed it to four groups of experts. Overall, the results show an agreement among experts that AI systems will probably reach overall human ability around 2040-2050, and move on to super-intelligence in less than 30 years thereafter. The experts say the probability is about one in three that this development turns out to be ‘bad’ or ‘extremely bad’ for humanity.

My guess (without checking the paper to see if they report it) is that test-retest correlation for chimps is well below the 0.9--0.95 often found for (human) g. Thus the h2 = 0.5 figure reported below could be significantly higher if corrected for reliability.

Nature News: Smart chimpanzees often have smart offspring, researchers suggest in one of the first analyses of the genetic contribution to intelligence in apes. The findings, published online today in Current Biology1, could shed light on how human intelligence evolved, and might even lead to discoveries of genes associated with mental capacity.

A team led by William Hopkins, a psychologist at Georgia State University in Atlanta, tested the intelligence of 99 chimpanzees aged 9 to 54 years old, most of them descended from the same group of animals housed at the Yerkes National Primate Research Center in Atlanta. The chimps faced cognitive challenges such as remembering where food was hidden in a rotating object, following a human’s gaze and using tools to solve problems.

A subsequent statistical analysis revealed a correlation between the animals' performance on these tests and their relatedness to other chimpanzees participating in the study. About half of the difference in performance between individual apes was genetic, the researchers found.

In humans, about 30% of intelligence in children can be explained by genetics; for adults, who are less vulnerable to environmental influences, that figure rises to 70%. Those numbers are comparable to the new estimate of the heritability of intelligence across a wide age range of chimps, says Danielle Posthuma, a behavioural geneticist at VU University in Amsterdam, who was not involved in the research.

“This study is much overdue,” says Rasmus Nielsen, a computational biologist at the University of California, Berkeley. “There has been enormous focus on understanding heritability of intelligence in humans, but very little on our closest relatives.”

Tuesday, July 08, 2014

A great MIT colloquium by Jim Simons (intro by I. Singer). Interesting discussion @28 min about how Simons (after leaving mathematics at 38) became an investor. Initially, he relied both on fundamental / event-driven analysis (reading the newspaper ;-) as well as computer models. But Simons eventually decided on a completely model-driven approach, and the rest is history.

@38 min: on RenTech's secret, We start with first rate scientists ... Great infrastructure ... New ideas shared and discussed as soon as possible in an open environment ... Compensation based on overall firm performance ...

@44 min: Be guided by beauty ... Try to do it RIGHT ... Don't give up and hope for some good luck!

Saturday, July 05, 2014

I came across a PDF version of this book online. It contains a number of fine essays, including the ones excerpted from below. A recurring question concerning Godel's incompleteness results is whether they impact "interesting" mathematical questions.

CHAPTER 21 The Godel Phenomenon in Mathematics: A Modern View: ... Hilbert believed that all mathematical truths are knowable, and he set the threshold for mathematical knowledge at the ability to devise a “mechanical procedure.” This dream was shattered by Godel and Turing. Godel’s incompleteness theorem exhibited true statements that can never be proved. Turing formalized Hilbert’s notion of computation and of finite algorithms (thereby initiating the computer revolution) and proved that some problems are undecidable – they have no such algorithms.

Though the first examples of such unknowables seemed somewhat unnatural, more and more natural examples of unprovable or undecidable problems were found in different areas of mathematics. The independence of the continuum hypothesis and the undecidability of Diophantine equations are famous early examples. This became known as the Godel phenomenon, and its effect on the practice of mathematics has been debated since. Many argued that though some of the inaccessible truths above are natural, they are far from what is really of interest to most working mathematicians. Indeed, it would seem that in the seventy-five years since the incompleteness theo- rem, mathematics has continued thriving, with remarkable achievements such as the recent settlement of Fermat’s last “theorem” by Wiles and the Poincare conjecture by Perelman. Are there interesting mathematical truths that are unknowable?

The main point of this chapter is that when knowability is interpreted by modern standards, namely, via computational complexity, the Godel phenomenon is very much with us. We argue that to understand a mathematical structure, having a decision pro- cedure is but a first approximation; a real understanding requires an efficient algorithm. Remarkably, Godel was the first to propose this modern view in a letter to von Neumann in 1956, which was discovered only in the 1990s.

Meanwhile, from the mid-1960s on, the field of theoretical computer science has made formal Godel’s challenge and has created a theory that enables quantification of the difficulty of computational problems. In particular, a reasonable way to capture knowable problems (which we can efficiently solve) is the class P, and a reasonable way to capture interesting problems (which we would like to solve) is the class NP. Moreover, assuming the widely believed P ̸= NP conjecture, the class NP -complete captures interesting unknowable problems. ...

This volume also includes Paul Cohen's essay (chapter 19) on his work on the Continuum Hypothesis and his interactions with Godel. See also Horizons of Truth.

Cohen: ... I still had a feeling of skepticism about Godel's work, but skepticism mixed with awe and admiration.

I can say my feeling was roughly this: How can someone thinking about logic in almost philosophical terms discover a result that had implications for Diophantine equations? ... I closed the book and tried to rediscover the proof, which I still feel is the best way to understand things. I totally capitulated. The Incompleteness Theorem was true, and Godel was far superior to me in understanding the nature of mathematics.

Although the proof was basically simple, when stripped to its essentials I felt that its discoverer was above me and other mere mortals in his ability to understand what mathematics -- and even human thought, for that matter -- really was. From that moment on, my regard for Godel was so high that I almost felt it would be beyond my wildest dreams to meet him and discover for myself how he thought about mathematics and the fount from which his deep intuition flowed. I could imagine myself as a clever mathematician solving difficult problems, but how could I emulate a result of the magnitude of the Incompleteness Theorem? There it stood, in splendid isolation and majesty, not allowing any kind of completion or addition because it answered the basic questions with such finality.

The reason why we find it possible to construct, say, electronic calculators, and indeed why we can perform mental arithmetic, cannot be found in mathematics or logic. The reason is that the laws of physics "happen" to permit the existence of physical models for the operations of arithmetic such as addition, subtraction and multiplication.

that suggests the primacy of physical reality over mathematics (usually the opposite assumption is made!) -- the parts of mathematics which are simply models or abstractions of "real" physical things are most likely to be free of contradiction or misleading intuition. Aspects of mathematics which have no physical analog (e.g., infinite sets) are prone to problems in formalization or mechanization. Physics (models which can to be compared to experimental observation; actual "effective procedures") does not ever require infinity, although it may be of some conceptual convenience. Hence one suspects, along the lines above, that mathematics without something like the "axiom of infinity" might be well-defined. Is there some sort of finiteness restriction (e.g., upper bound on Godel number) that evades Godel's theorem? If one only asks arithmetical questions about numbers below some upper bound, can't one avoid undecidability?

Tuesday, July 01, 2014

Alternet: ... According to The Sunday Times of London, Glenn Greenwald will publish the names of Americans targeted by the NSA.

“One of the big questions when it comes to domestic spying is, ‘Who have been the NSA’s specific targets?’” he told the Times. “Are they political critics and dissidents and activists? Are they genuinely people we’d regard as terrorists? What are the metrics and calculations that go into choosing those targets and what is done with the surveillance that is conducted? Those are the kinds of questions that I want to still answer.”

Greenwald has promised that this will be the “biggest” revelation of the nearly two million classified files he received from Edward Snowden, and that “Snowden’s legacy would be ‘shaped in large part’ by this ‘finishing piece’ still to come.” In a May interview with GQ, Greenwald spoke of this “finale:”

"I think we will end the big stories in about three months or so [June or July 2014]. I like to think of it as a fireworks show: You want to save your best for last. There's a story that from the beginning I thought would be our biggest, and I'm saving that. The last one is the one where the sky is all covered in spectacular multicolored hues. This will be the finale, a big missing piece. Snowden knows about it and is excited about it."

My high school fight song. Legend says it was written in the counterculture 60's and that some wag managed to slip "comrades at work and at play" into the lyrics under the noses of the school administrators. It's just the kind of thing clever AHS students might attempt :-)